Context

The 2017 Census of Pakistan was a detailed enumeration of the Pakistani population which began on 15 March 2017 and ended on 25 May 2017. It was the first census taken in the country in the 21st century, nineteen years after the previous one in 1998, and it was carried out by the Pakistan Bureau of Statistics.

Source

The data has been collected from the official website of the Pakistan Bureau of Statistics. Link: https://www.pbs.gov.pk/content/final-results-census-2017

Acknowledgments

Thanks to all who take their time and energy to perform Kernels with this dataset and reviewers.

Inspiration

I would like the community to feel free to explore the provided dataset and use it to polish your statistical skills.

Abstract

The Pakistan Demographic and Health Survey PDHS 2017-18 was the fourth of its kind in Pakistan, following the 1990-91, 2006-07, and 2012-13 PDHS surveys.

The primary objective of the 2017-18 PDHS is to provide up-to-date estimates of basic demographic and health indicators. The PDHS provides a comprehensive overview of population, maternal, and child health issues in Pakistan. Specifically, the 2017-18 PDHS collected information on:

• Key demographic indicators, particularly fertility and under-5 mortality rates, at the national level, for urban and rural areas, and within the country’s eight regions
• Direct and indirect factors that determine levels and trends of fertility and child mortality
• Contraceptive knowledge and practice
• Maternal health and care including antenatal, perinatal, and postnatal care
• Child feeding practices, including breastfeeding, and anthropometric measures to assess the nutritional status of children under age 5 and women age 15-49
• Key aspects of family health, including vaccination coverage and prevalence of diseases among infants and children under age 5
• Knowledge and attitudes of women and men about sexually transmitted infections (STIs), including HIV/AIDS, and potential exposure to risk
• Women's empowerment and its relationship to reproductive health and family planning
• Disability level
• Extent of gender-based violence
• Migration patterns

The information collected through the 2017-18 PDHS is intended to assist policymakers and program managers at the federal and provincial government levels, in the private sector, and at international organisations in evaluating and designing programs and strategies for improving the health of the country’s population. The data also provides information on indicators relevant to the Sustainable Development Goals.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-49

Universe

The survey covered all de jure household members (usual residents), children age 0-5 years, women age 15-49 years and men age 15-49 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2017-18 PDHS is a complete list of enumeration blocks (EBs) created for the Pakistan Population and Housing Census 2017, which was conducted from March to May 2017. The Pakistan Bureau of Statistics (PBS) supported the sample design of the survey and worked in close coordination with NIPS. The 2017-18 PDHS represents the population of Pakistan including Azad Jammu and Kashmir (AJK) and the former Federally Administrated Tribal Areas (FATA), which were not included in the 2012-13 PDHS. The results of the 2017-18 PDHS are representative at the national level and for the urban and rural areas separately. The survey estimates are also representative for the four provinces of Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan; for two regions including AJK and Gilgit Baltistan (GB); for Islamabad Capital Territory (ICT); and for FATA. In total, there are 13 secondlevel survey domains.

The 2017-18 PDHS followed a stratified two-stage sample design. The stratification was achieved by separating each of the eight regions into urban and rural areas. In total, 16 sampling strata were created. Samples were selected independently in every stratum through a two-stage selection process. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units at different levels, and by using a probability-proportional-to-size selection at the first stage of sampling.

The first stage involved selecting sample points (clusters) consisting of EBs. EBs were drawn with a probability proportional to their size, which is the number of households residing in the EB at the time of the census. A total of 580 clusters were selected.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 28 households per cluster was selected with an equal probability systematic selection process, for a total sample size of approximately 16,240 households. The household selection was carried out centrally at the NIPS data processing office. The survey teams only interviewed the pre-selected households. To prevent bias, no replacements and no changes to the pre-selected households were allowed at the implementing stages.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Six questionnaires were used in the 2017-18 PDHS: Household Questionnaire, Woman’s Questionnaire, Man’s Questionnaire, Biomarker Questionnaire, Fieldworker Questionnaire, and the Community Questionnaire. The first five questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Pakistan. The Community Questionnaire was based on the instrument used in the previous rounds of the Pakistan DHS. Comments were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. The survey protocol was reviewed and approved by the National Bioethics Committee, Pakistan Health Research Council, and ICF Institutional Review Board. After the questionnaires were finalised in English, they were translated into Urdu and Sindhi. The 2017-18 PDHS used paper-based questionnaires for data collection, while computerassisted field editing (CAFE) was used to edit the questionnaires in the field.

Cleaning operations

The processing of the 2017-18 PDHS data began simultaneously with the fieldwork. As soon as data collection was completed in each cluster, all electronic data files were transferred via IFSS to the NIPS central office in Islamabad. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors. Secondary editing was carried out in the central office, which involved resolving inconsistencies and coding the openended questions. The NIPS data processing manager coordinated the exercise at the central office. The PDHS core team members assisted with the secondary editing. Data entry and editing were carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage as it maximised the likelihood of the data being error-free and accurate. The secondary editing of the data was completed in the first week of May 2018. The final cleaning of the data set was carried out by The DHS Program data processing specialist and completed on 25 May 2018.

Response rate

A total of 15,671 households were selected for the survey, of which 15,051 were occupied. The response rates are presented separately for Pakistan, Azad Jammu and Kashmir, and Gilgit Baltistan. Of the 12,338 occupied households in Pakistan, 11,869 households were successfully interviewed, yielding a response rate of 96%. Similarly, the household response rates were 98% in Azad Jammu and Kashmir and 99% in Gilgit Baltistan.

In the interviewed households, 94% of ever-married women age 15-49 in Pakistan, 97% in Azad Jammu and Kashmir, and 94% in Gilgit Baltistan were interviewed. In the subsample of households selected for the male survey, 87% of ever-married men age 15-49 in Pakistan, 94% in Azad Jammu and Kashmir, and 84% in Gilgit Baltistan were successfully interviewed.

Overall, the response rates were lower in urban than in rural areas. The difference is slightly less pronounced for Azad Jammu and Kashmir and Gilgit Baltistan. The response rates for men are lower than those for women, as men are often away from their households for work.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017-18 Pakistan Demographic and Health Survey (2017-18 PDHS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017-18 PDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that

Abstract

The MICS Punjab, 2017-18 has as its primary objectives:

• To provide high quality data for assessing the situation of children, adolescents, women and households in Punjab;

• To furnish data needed for monitoring progress toward national goals, as a basis for future action;

• To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable;

• To validate data from other sources and the results of focused interventions;

• To generate data on national and global SDG indicators;

• To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention;

• To generate behavioural and attitudinal data not available in other data sources.

Geographic coverage

The sample for the MICS Punjab, 2017-18 was designed to provide estimates for a large number of indicators on the situation of children and women at the Punjab level, for urban and rural areas, and for all 36 districts of Punjab.

Analysis unit

• Individuals

• Households

Universe

The survey covered all de jure household members (usual residents), all women age 15-49 years, all men age 15-49 years, all children under 5 and children age 5-17 years living in the household.

Sampling procedure

The urban and rural areas within each district were identified as the main sampling strata, and the sample of households was selected in two stages. Within each stratum, a specified number of census enumeration areas were selected systematically with probability proportional to size. Using the listing of households from the Census 2017 for each sample enumeration area, provided by Pakistan Bureau of Statistics, a systematic sample of 20 households was drawn in each sample enumeration area1. The total sample size was 53,840 households in 2,692 sample clusters. All the selected enumeration areas were visited during the fieldwork period. As the sample is not self-weighting, sample weights are used for reporting survey results.

Mode of data collection

Face-to-face [f2f]

Research instrument

Six questionnaires were used in the survey: 1) a household questionnaire to collect basic demographic information, the household, and the dwelling; 2) a water quality testing questionnaire administered in three households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) a questionnaire for individual men administered in every second household to all men age 15-49 years; 5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

Cleaning operations

Data were received at the Bureau of Statistics, Punjab via Internet File Streaming System (IFSS) integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to the editing process described in detail in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 24 Model syntax and tabulation plan developed by UNICEF were customised and used for this purpose.

Response rate

Response rate (Households): 97.9%

Abstract

The 2019 Pakistan Maternal Mortality Survey (2019 PMMS) was the first stand-alone maternal mortality survey conducted in Pakistan. A nationally representative sample of 1,396 primary sampling units were randomly selected. The survey was expected to result in about 14,000 interviews with ever-married women age 15-49.

The primary objective of the 2019 PMMS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the survey was designed and carried out with the purpose of assessing where Pakistan stands on maternal health indicators and how well the country is moving toward these targets. Overall aims of the 2019 PMMS were as follows: - To estimate national and regional levels of maternal mortality for the 3 years preceding the survey and determine whether the MMR has declined substantially since 2006-07 - To identify medical causes of maternal deaths and the biological and sociodemographic risk factors associated with maternal mortality - To assess the impact of maternal and newborn health services, including antenatal and postnatal care and skilled birth attendance, on prevention of maternal mortality and morbidity - To estimate the prevalence and determinants of common obstetric complications and morbidities among women of reproductive age during the 3 years preceding the survey

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Woman age 15-49
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2019 PMMS used a multistage and multiphase cluster sampling methodology based on updated sampling frames derived from the 6th Population and Housing Census, which was conducted in 2017 by the Pakistan Bureau of Statistics (PBS). The sampling universe consisted of urban and rural areas of the four provinces of Pakistan (Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan), Azad Jammu and Kashmir (AJK), Gilgit Baltistan (GB), Federally Administered Tribal Areas (FATA), and the Islamabad Capital Territory (ICT). A total of 153,560 households (81,400 rural and 72,160 urban) were selected using a two-stage and two-phase stratified systematic sampling approach. The survey was designed to provide representative results for most of the survey indicators in 11 domains: four provinces (by urban and rural areas with Islamabad combined with Punjab and FATA combined with Khyber Pakhtunkhwa), Azad Jammu and Kashmir (urban and rural), and Gilgit Baltistan. Restricted military and protected areas were excluded from the sample.

The sampled households were randomly selected from 1,396 primary sampling units (PSUs) (740 rural and 656 urban) after a complete household listing. In each PSU, 110 randomly selected households were administered the various questionnaires included in the survey. All 110 households in each PSU were asked about births and deaths during the previous 3 years, including deaths among women of reproductive age (15-49 years). Households that reported at least one death of a woman of reproductive age were then visited, and detailed verbal autopsies were conducted to determine the causes and circumstances of these deaths to help identify maternal deaths. In the second phase, 10 households in each PSU were randomly selected from the 110 households selected in the first phase to gather detailed information on women of reproductive age. All eligible ever-married women age 15-49 residing in these 10 households were interviewed to gather detailed information, including a complete pregnancy history.

Note: A detailed description of the sample design is provided in Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Six questionnaires were used in the 2019 PMMS: the Short Household Questionnaire, the Long Household Questionnaire, the Woman’s Questionnaire, the Verbal Autopsy Questionnaire, the Community Questionnaire, and the Fieldworker Questionnaire. A Technical Advisory Committee was established to solicit comments on the questionnaires from various stakeholders, including representatives of government ministries and agencies, nongovernmental organisations, and international donors. The survey protocol was reviewed and approved by the National Bioethics Committee, the Pakistan Health Research Council, and the ICF Institutional Review Board. After being finalised in English, the questionnaires were translated into Urdu and Sindhi. The 2019 PMMS used paper-based questionnaires for data collection, while computer-assisted field editing (CAFE) was used to edit questionnaires in the field.

Cleaning operations

The processing of the 2019 PMMS data began simultaneously with the fieldwork. As soon as data collection was completed in each cluster, all electronic data files were transferred via the Internet File Streaming System (IFSS) to the NIPS central office in Islamabad. These data files were registered and checked for inconsistencies, incompleteness, and outliers. A double entry procedure was adopted by NIPS to ensure data accuracy. The field teams were alerted about any inconsistencies and errors. Secondary editing of completed questionnaires, which involved resolving inconsistencies and coding open-ended questions, was carried out in the central office. The survey core team members assisted with secondary editing, and the NIPS data processing manager coordinated the work at the central office. Data entry and editing were carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage because it maximised the likelihood of the data being error-free and accurate.

Response rate

In the four provinces, the sample contained a total of 116,169 households. All households were visited by the field teams, and 110,483 households were found to be occupied. Of these households, 108,766 were successfully interviewed, yielding a household response rate of 98%. The subsample selected for the Long Household Questionnaire comprised 11,080 households, and interviews were carried out in 10,479 of these households. A total of 12,217 ever-married women age 15-49 were eligible to be interviewed based on the Long Household Questionnaire, and 11,859 of these women were successfully interviewed (a response rate of 97%).

In Azad Jammu and Kashmir, 16,755 households were occupied, and interviews were successfully carried out in 16,588 of these households (99%). A total of 1,707 ever-married women were eligible for individual interviews, of whom 1,666 were successfully interviewed (98%). In Gilgit Baltistan, 11,005 households were occupied, and interviews were conducted in 10,872 households (99%). A total of 1,219 ever-married women were eligible for interviews, of whom 1,178 were successfully interviewed (97%).

A total of 944 verbal autopsy interviews were conducted in Pakistan overall, 150 in Azad Jammu and Kashmir, and 88 in Gilgit Baltistan. The Verbal Autopsy Questionnaire was used in almost all of the interviews, and response rates were nearly 100%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2019 Pakistan Maternal Mortality Survey (2019 PMMS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2019 PMMS is only one of many samples that could have been selected from the same population, using the same design and sample size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019 PMMS sample was the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS programmes developed by ICF. These programmes use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios and use the Jackknife repeated replication method for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey report.

Data appraisal

Data Quality Tables

- Household age distribution